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Asian Economic and Financial Review, 2013, 3(3):341-354
Asian Economic and Financial Review
journal homepage: http://aessweb.com/journal-detail.php?id=5002
THE EFFECT OF INTEREST RATE, INFLATION RATE, GDP, ON REAL
ECONOMIC GROWTH RATE IN JORDAN
Abdul Aziz Farid Saymeh
Dept. of Accounting and Finance, Middle East University
Marwan Mohammad Abu Orabi
Dept. of Finance and Business, the World Islamic Science University
ABSTRACT
The main objective of this study is to investigate the effect of interest rate, inflation rate, and GDP
on real economic growth in Jordan over the period 2000-2010. Unit root test (Augmented DickeyFuller test) has been exploited to check the integration order of the variables. Acointegration
analysis with four variables (economic growth, interest rate, GDP, and inflation level) is employed.
Study adopted Johansen test. Findings indicated that both trace test and max eigenvalue static
showed that the four equations have significant existent 1% or 5%. It means that all variables have
long term equilibrium relationship. Study adopted the same four variables to discuss Granger
Causality relationship; findings indicated that inflation causes interest rate. On the other hand all
other variables are independent with each other. Regressionwas conducted to test growth rate with
interest rate which showed that current interest rate has an influence power on growth rate. Also,
regression used to test growth rate with inflation rate; it showed that inflation rate has influence
power on growth rate. Finally regression used to test GDP, interest rate, and inflation rate
together; results have shown that current GDP and one lag GDP have influence power to growth
rate.
Keywords: Inflation, Economic Growth, Interest Rate, GDP
JEL Classification: E31, 040, E43, E01
INTRODUCTION
Economic growth of any country reflects its capacity to increase production of goods and services.
The simplest definition of economic growth can be stated as the increase in the Gross Domestic
Product (GDP) of that country. Nominal GDP is usually adjusted for inflation factor to reflect real
GDP. Interest rate is one of the macroeconomic growth factors; it’s up and down volatility is
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closely related with inflation rates. Its high or low rates also impact the economic boom (high
GDP) and extending to influence economic growth rate. In business fields, it is very important to
accurately predict interest rate trends. Many previous studies have assumed that the time series data
is stationary and they ignored that non stationary could exist in the variables. This study is a
contribution to the existing literature on real growth applied to Jordan’s economy; it will examine
the effect of interest rate, inflation, and Real GDP on the real growth rate of Jordan’s economic.
Study is concerned to analyze:
-
The relationship between Interest rate and inflation rate,
-
The relationship between GDP and economic growth rate.
-
The Effect of Interest rate, Inflation rate, and R. GDP, on Real Economic Growth Rate.
Research Problem
Measuring real economic growth of a country aims to assess whether growth can cope with the
growing demands of the society including the population and prosperity growth rates; and how to
maintain and confine the depletion rate of its national natural resources.
This study is designed to investigate the effect of the basic economic factors such as interest rate,
inflation rate, and GDP on Jordan’s real economic growth by answering the following questions:
1-Is the effect of inflation on real economic growth rate significant?
2- Is the effect of interest rate on real economic growth rate significant?
3-Is the effect of R.GDP on real economic growth rate significant?
LITERATURE REVIEW
Previous Studies
Estrella and Hardouvelis (1991). Tested data over the period 1955 to 1988, they found out that the
spread between the yield on the ten year Treasury bond and the three-month Treasury bill is a
useful predictor of both cumulative economic growth up to four years in the future and marginal
economic growth rates up to seven quarters in the future. They also found that the spread contains
information for future economic growth. Spread was not a very good predictor of economic activity
over the period 1985 to 1995. Haubrich and Dombrovsky (1996): they tested for yield spread over
the period 1961:1 to 1995:3, they found that the yield spread is a relatively accurate predictor of
four-quarter economic growth; but this predictive content has changed over time. Berument (1999):
Researcher indicated inflation rate influenced three month Treasury bill rate by using conditional
variance of inflation rate to represent risk index. The results showed inflation rate had positive
influence to three month Treasury bill rate. Sweidan (2004): Researcher aimed to check whether
inflation and economic growth have a structural break point effect. He found that there is a positive
structural effect at inflation rate of 2%, while at higher rates effect turned to be negative; so he
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recommended that Central Bank of Jordan should pay attention to the inflation phenomenon while
conducting new monetary policies. Engen and Hubbard ( 2004): Researchers have determined that
an increase in federal government debt equivalent to one percent of GDP, all else equal, would be
expected to increase the long-term real rate of interest by about three basis points. Giovanni and
Shambaugh (2007): This paper explored the connection between interest rates in major industrial
countries and annual real output growth in other countries. The results show that high foreign
interest rates have a contractionary effect on annual real GDP growth in the domestic economy, but
that this effect is centered on countries with fixed exchange rates. The paper then examines the
potential channels through which major-country interest rates affect other economies. The effect of
foreign interest rates on domestic interest rates is the most likely channel when compared with
other possibilities, such as a trade effect. Tridico (2007): Researcher explained economic growth is
a complex issue which needs positive interaction of several socio-economic and institutional
factors. His analysis suggested that countries can grow with their own “style of capitalism” and
economic model, and the determinants of economic growth seem to be the ability of each country
to associate appropriate governance and institutions with education level, export activity and nonincome dimensions of human development (life expectancy growth and infant mortality reduction).
In fact, countries which experienced an increase in non-income dimensions of human development
during 1970-2000 as a consequence of appropriate institutions, have sustained economic growth.
(Hasanov, 2010): The study examined possibility of threshold effect of inflation on economic
growth in Azerbaijani economy over the period of 2000-2009. Estimated threshold model indicated
that there is a non-linear relationship between economic growth and inflation in the Azerbaijani
economy and threshold level of inflation for GDP growth is 13 percent. Below threshold level
inflation has statistically significant positive effect on GDP growth, but this positive relationship
becomes negative one when inflation exceeds 13 percent. Nisha and Nishat (2011) found that
economic activities can be created by flow of reserves to the most productive investments, as
investors usually decide to invest in certain selected companies. Shahmoradi and Baghbanyan
(2011) concentrated on the determining factors of foreign direct investment inflows in developing
countries, study was conducted for the period 1990-2007. Obamuyi and Olorunfemi (2011)
examined the implications of financial reform and interest rate behavior on the economic growth in
Nigeria. Study results revealed that financial reform and interest rates have significant impact on
economic growth in Nigeria; also, results implied that the interest rate behavior is important for
economic growth.
Test Hypotheses
Ho-1: There is no significant effect of interest rate on economic growth.
Ho-2: There is no significant effect of inflation on economic growth.
Ho-3: There is no significant effect of GDP on economic growth.
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METHODOLOGY
Data
Data was collected from Central Bank Files: Nominal Interest rates, Inflation rates,CPI(consumer
price index) and GDP rates for the period 2000- 2010.
Tests
Researchers used unit root test to distinguish ifdata have stationary ACF or PACF figure diagnosis.
It is too arbitrary to use figure diagnosis to judge variable’s stationary. The study will use
Augmented Dickey and Fuller test (ADF) that it is purposed to eliminate error term correlations.
The model has three styles shown below.
A.
B.
C.
no intercept and no time trend items: yt   yt 1 
p
  y
intercept and no time trend item: yt     yt 1 
t 1
t
t 1
 t
p
  y
t 1
intercept and time trend item: yt     t   yt 1 
t 1
t
 t
p
  y
t 1
t
t 1
 t
The study used unit root process allowing for intercept and time trend to determine whether there is
a unit root in the data series. Tochoose the lag length;study adopted Augmented Dickey and Fuller
tests (ADF); the model is shown below:
SBC ( p)  N log(SSR)  p log N , Whereas p is volume of parameter, N is sample size, and
SSR is sum of square residual.
Co integration Test
The study adopted Johansen multivariate maximum likelihood method using this co integration
process to test the variables with existed long term equilibrium relationship. First step used first
difference in the vector autoregressive model, the formulasare shown below:
Yt  AY
1 t 1  A2Yt  2  ....  AnYt  n   t , Whereas Yt is lag length n ( p 1) vector endogenous
n 1
Yt    j Yt  j   Yt  n   t , whereas  j is a short term adjusting coefficient to describe
j 1
short-term relationship,
 is long term shock vector that includes long term information hint in
the regression to test those variables’ whether existence long term equilibrium relationship or not.
Meanwhile rank of
 decides the number of co integrated vector. It has three kinds of styles:
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a. rank ( )  n then  is full rank. It means all of variables are stationary series in the regression
( Yt )
b. rank ( )  0 , then
 is null rank. It means variables do not have co integrated relationship.
c. 0  rank ( )  r  n , then some of variables exist r co integrated vector. Johansen approach
has used rank of
 to distinguish the number of co integrated vector. To examine the vector rank
that tests how many non-zero characteristic roots existed in the vector. It could use below two
statistic processes co integration.
a.
Trace test:
H 0 : rank ( )  r (at most r integrated vector)
H1 : rank ( )  r (at least r+1 integrated vector)
n
trace (r )  T  ln(1  ˆi )
i  r 1
T is sample size,
ˆi
is estimated of characteristic root. If test rejects
H 0 that means variables
exist at least r+1 long term co integrated relationship.
b. Maximum cointegration value test:
H 0 : rank ( )  r (at most r integrated vector)
H1 : rank ( )  r (at least r+1 integrated vector)
max (r, r 1)  T ln(1  ˆr 1 )
If test accept
H 0 that means variables have r co integrated vector. The method is starting test
from variables do not have any co integrative relationship which is r=0. Then test has added the
number of co integrative item till can’t reject
H 0 that means variables have r co integrated vector.
Granger Causality Test
Many models assume different hypotheses to discuss variables’ relationship; but they could not
make sure variables’ cause and effect relationship. However, Granger (1969). was the first person
who defined lead and lag relations based on the role of predictability; He used twin factors of VAR
to find variables’ causal relationship. This test assumed two series X t and
Yt
that define those
messages set.
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k
k
i 1
i 1
k
k
i 1
i 1
X t   0   1i X t 1    2iYt 1  1t
Yt   0   1i X t 1    2iYt 1   2t
To test four coefficients find out variables’ relationship.
d.
a.
 2i  0 and 1i  0 : It means Y lead X or X lag Y.
b.
1i  0 and  2i  0 : It means X lead Y or Y lag X.
c.
 2i  0 and 1i  0 : It means both of variables are independent.
 2i  0 and 1i  0 :
It means both of variables are interactive each other and have
feedback relationship.
Series Autocorrelation
Ljung and Box (1978): Researchers have brought up the Ljung-Box Q. test to examine if data
series have autocorrelation or linear dependence existence. The test formula is:
q
Q  T (t  2) rk2 /(T  K ) ~  2 (q ) , Whereas T is sample size and q is time lag length. As
k 1
model rejects
H 0 that means series has correlative existence.
Generalized Autoregressive Conditional Heteroskedasti city (GARCH) Process
An econometric term developed in 1982 by Robert F. Engle, to describe an approach to estimate
volatility in financial markets. There are several forms of GARCH modeling. The GARCH process
provides a more real-world context to predict the prices and rates of financial instruments. The
general process for a GARCH model involves three steps. The first is to estimate a best-fitting
autoregressive model; secondly, compute autocorrelations of the error term and lastly, test for
significance. Based on Engel (2005). and (Bollerslev, 1986): Researchershave suggested LM test to
examine GARCH effect existence . The test hypothesis is:
H 0 : No ARCH effect existence
Rt     t
q
 t2   0   i t2i  et
i 1
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Owning to above LM test indicates the statistic is
TR 2 ~  2 (q) . If TR 2   2 (q) then model
needs to reject
H 0 that series regression have to consider ARCH effect existence. Whereas T is
sample size and
statistic.
R 2 is regression’s coefficient. That two times together is ARCH LM test’s TR 2
Generalized Autoregressive Conditional Heteroskedasti city (GARCH) Model
The conditional variance is influence past p period of residual error term and past q period of
conditional variance.
GARCH ( p, q)
Rt  aX t   t ,  t | t 1 ~ N (0, ht )
ht   0  1 t21  ....   q t2 q  1ht 1  ...   p ht  q
q
= 0    
i 1
Whereas
2
i t q
p
   j ht 1
j 1
Rt is variable X t exogenous, t 1 is all collected messages till t-1 period, aX t is
conditional mean that is the linear portfolio of exogenous and endogenous variables, and
ht is
conditional variance that it influenced by past q period sum of squared error term and past p period
of itself conditional heteroskedasticity.
TEST RESULTS AND ANALYSIS
Table-1. Compiled Data set
year
Nominal
Interest (%)
Nomin
al
GDP
Cpi*
Real GDP
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
5.75
3.88
2.88
2.12
2.805
4.629
6.495
5.147
4.645
2.645
2.15
5154
5470
5850
6301
7195
7964
9363
10805
13971
15045
16417
0.84
0.85
0.87
0.89
0.91
0.94
1.0
1.05
1.19
1.19
1.25
6135.714
6435.294
6724.138
7079.775
7906.593
8472.34
9363
10290.48
11740.34
12642.86
13133.6
Real
Economic
Growth
(∆GDP)%
---4.8826
4.4884
5.2890
11.6786
7.1554
10.5126
9.9058
14.0893
7.6874
3.8816
Inflation (%)
0.70
1.8
1.8
1.6
2.6
3.5
6.25
4.7
13.9
-0.7
----
*:Cpi: consumer price index,data was compiled as follows:
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Asian Economic and Financial Review, 2013, 3(3):341-354
-
Real GDP was calculated by dividing nominal GDP by CPI index.
-
Economic growth rate was calculated by using the mathematical formula:
-
Real economic growth = [(real GDPt – real GDPt-1)\real GDPt-1] x100%
Analysis of Data
This study adopts data from Jordanian central bank and research period from 2000 to 2010. The
main purpose in this study tries to find the effect of economic factors: realGDP, interest rate and
inflation, on real growth rate. Table 2 is four variables’ descriptive statistics .It finds growth rate
and inflation are non-normal distribution, but GDP and interest rate are normally distributed
because J-B ratio is significant. According to Kurtosis all variables appear leptokurtic phenomena.
Table-1. The Descriptive Statistics of Variables
Growth GDP
INF
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
Jarque-Bera
Probability
Sum
Sum Sq. Dev.
Observations
10.46771
8.675644
27.88530
2.999918
6.849994
1.351753
3.900093
6.765927
0.033947
209.3542
891.5258
20
8075.192
6181.158
19527.88
2958.000
4862.384
1.211097
3.255807
4.943715
0.084428
161503.8
4.49E+08
20
3.782500
3.150000
13.90000
-0.700000
3.212282
1.592657
6.046742
16.19072
0.000305
75.65000
196.0564
20
INT
6.311500
6.400000
12.08000
-4.490000
3.775792
-1.013095
4.420739
5.103286
0.077953
126.2300
270.8755
20
Table 3below indicates that all variables do not reject unit root null hypothesis except inflation.
This means that variables - other than inflation – in the level stage are of non-stationary existence.
First difference I (1) in the Unit root test showed that all of variables achieved1% significant level.
The lag length for growth rate is 0, GDP - 3, inflation - 0, interest rate - 1.
Table-2. Unit Root Test Based on Augmented Dickey-Fuller test and Lag Length Based on
Schwartz Bayesian Information Criterion
Level I(0)
Growth Rate
-2.435994
(0.14892)
GDP
-0.058033
(0.9388)
Inflation Rate
-5.022752
(0.0007)
Interest Rate
-2.476788
(0.1362)
First Difference I(1)
-9.814166***
(0.0000)
-3.665997**
(0.0163)
-7.670441***
(0.0000)
-7.360783***
(0.0000)
Lag Length
I(1)
0
I(1)
3
I(1)
0
I(1)
1
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Table-4: co integration test is conducted to examine if variables have long term equilibrium
relationship. This study adopted Johansentest, results are show in table 3. From the findings, it has
been realized that no matter which is traced, Eigen value static showed four equations have
significant existent at 1%,5%, and 10%. This means that all variables have long term equilibrium
relationship.
Table-3. Panel A: Unrestricted Co integration Rank Test
Hypothesized Number of Co Eigen value
Trace Statistic
5%
Critical
integrating Equations
Value
None **
0.956544
87.85933
47.85613
At most 1 **
0.588692
31.41123
29.79707
At most 2 ***
0.392923
15.41979
15.49471
At most 3 *
0.300616
6.436003
3.841466
1% Critical
Value
0.0000
0.0323
0.0513
0.0112
*(**) denotes rejection of the hypothesis at the 5 %, 10 %( 1%) level
Hypothesized Number of
Co integrating Equations
None **
At most 1 **
At most 2 *
At most 3 *
Table-3. Panel B:
Eigen value
Max-Eigen
Statistic
0.956544
56.44811
0.588692
15.99143
0.392923
8.983789
0.300616
6.436003
5% Critical
Value
27.58434
21.13162
14.26460
3.841466
1% Critical
Value
0.0000
0.2253
0.2875
0.0112
*(**) denotes rejection of the hypothesis at the 5 %( 1%) level
Table 5 below showed that study adopted Pair wise Granger Causality test to examine the causal
relations between interest rate and inflation rate, GDP, and real growth rate. Study adopted four
variables which are real growth rate, GDP, inflation and interest rate. Results indicated that
inflation caused interest rate. Also findings indicated that GDP Granger caused interest rate, real
growth rate, Granger caused inflation rate, and real growth rate and interest rate had feedback
relationship that each one caused to the other, this was shown by the flow chart below. On the other
hand all other variables were independent to each other; inflation with GDP, real growth rate with
GDP, and interest rate with inflation rate, all are independent. Also, interest rate did not cause GDP
and inflation rate did not cause real growth rate.
Table-4. Pair wise Granger Causality
Null Hypothesis
Obs
GDP does not Granger Cause G
18
G does not Granger Cause GDP
INF does not Granger Cause GDP
19
GDP does not Granger Cause INF
INT does not Granger Cause INF
19
INF does not Granger Cause INT
G does not Granger Cause INT
18
F-test
0.18513
1.16672
0.52893
0.51359
2.13153
6.99442
0.70384
P-value
0.8332
0.3420
0.6006
0.6092
0.1556
0.0078
0.5126
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INT does not Granger Cause G
INT does not Granger Cause GDP
GDP does not Granger Cause INT
19
1.18132
2.28287
1.91029
0.3378
0.1386
0.1847
Following flow chart shows the lead-lag relationship
Real Growth rate
Inflation rate
Figure-1. Flow Chart for Granger Causality relationship
Table 6: panel A showed: R square of GDP, interest rate, and inflation rate were 0.942, 0.492, and
0.386 consequently. From the regression test, growth rate with GDP relationship showed a current
and one lag, GDP had influenced growth rate with coefficients 0.009662 and -0.01059, t-test
results: 12.77989 and -8.53333. From the regression test, growth rate and interest rate showed that
current interest rate had influence power on growth rate; coefficient and t-test were: -1.196347 and
-3.575196. Also regression test, growth rate and inflation showed that inflation rate had influence
power on growth rate; coefficient and t-test were 1.323841 and 3.359709. Finally GDP, interest
rate, and inflation together to run regression test showed that current GDP and one lag GDP have
influence power to growth rate.
After running regression study process, it needs to examine Ljung-Box and ARCH effect to check
whether regression exists autocorrelation or heteroskedasticity phenomena. Panel B showed that
there were no regressions’ LB2 (12) existed in significance; this means that regressions did not
reflect an autocorrelation situation. However, interest rate had ARCH effect existence, which
means regression needed to adjust autoregressive conditional heteroskedasticity. After regressions
runs test: GARCH (1, 1) indicated one lag of interest rate had influence power on growth rate. LB2
(12) and ARCH found that all regressions had no significant p value existence; this means that all
regressions had adjusted and coefficients were more accurate to reflect real situation.
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Table-5: Panel A; The regression of growth rate (G) with GDP, (INT), and (INF)
Table-5: Panel B; after using GARCH (1, 1) to run the regression of growth rate (G) with gross
domestic product GDP, interest rate (INT), and inflation rate (INF).
The summary of this part uses regression to discuss the relation between: growth rate and GDP,
interest rate and inflation. Findings indicated that: current GDP, one lag of GDP, current interest
rate, one lag interest rate, and current inflation could have influence power on interest rate. All
regressions of GARCH runs model showed that variables were of no volatility or spillover effect
existence in the regressions.
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FINDINGS
The main purpose in this study tries to find out the effect of real GDP, interest rate, and inflation on
real economic growth in Jordan. Study had adopted a set of econometric tools such as: Unit root,
Cointegration test, Granger Causality, ARCH effect, Ljung-Box Q statistic, and GARCH model. In
order to obtain accurate results, researchers had to analyze the relationship between econometric
factors which are: interest rate, inflation rate, GDP, and real growth rate. From unit root method,
the study adopted ADF unit root to test the results that all of variables were belonging to I (1)
structure and lag length in interest rate was 0, inflation rate was 3, GDP was 1, and real growth rate
was 0.
Co integration tests: the study adopted cointegration test to examine whether the five variables had
long term equilibrium relationship. The findings indicated that all the variables in this test had
significant existence in co integrated vector. This means that all the variables had long term
equilibrium existence. Granger Causality examined the causal relations between interest rate and
inflation rate, GDP, and real growth rate. The findings indicated that GDP was affected by interest
rate and real growth rate was affected by inflation rate. Meanwhile interest rate and real growth rate
had feedback relation existence. However, this study proved that interest rate and real growth rate
have interdependent lead and lag relationship. Regressionshadtested variables’ relations and had
indicated one and two lags of inflation rates which influenced current interest rate and one lag of
GDP had influenced power to current interest rate.
According to all the regressions which included ARCH effect and variables did not have the
volatility or spillover risk existence after test GARCH (1, 1). However testing the regressions
indicated that interest rate and inflation rate had some kind of relations. Granger Causality had
adopted Granger Causality to examine the causal relations between interest rate and inflation rate,
GDP, and real growth rate. The findings indicated that GDP did cause interest rate and real growth
rate did cause inflation rate. Meanwhile interest rate and real growth rate had feedback relation
existence. The results seem like Mundell theory that: interest rate did not have the same pace with
inflation rate.
One thing was proved by this study that interest rate with real growth rate have lead and lag
relationship with each other. From the regressions of testing those variables; relations indicated one
and two lag of inflation rate had influenced the current interest rate and one lag of GDP also had
certainly influenced the power of current interest rate. All regressions had shown ARCH effect
existence while some variables did not show the volatility or spillover risk existence after test
GARCH (1, 1). However some regression tests indicated that interest rate and inflation rate had
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some kinds of relations; one or two lag of inflation rates had shown significant power to explain
interest rate.
CONCLUSIONS
Many macroeconomic theories tried to find the interrelationship between interest rate, GDP,
inflation, and real economic growth. Fisher (1930) suggested that expected interest rates change in
proportion to the changing expected inflation, or expected real interest rates are invariant to the
expected inflation rates. Mundell (1963) concluded that: nominal interest rate and expected
inflation rate do not have one to one adjustable relationships. This study, investigated the effect of
interest rate, inflation, and GDP on Jordan’s economic growth over the period of 2000-2010.It is
well known that regional economy is not yet out of the woods and since the global recovery from
last recession seems to have encountered further delays; economic growth outlook for Jordan is
increasingly challenging. Although adverse external environment continues to add to domestic
uncertainties associated with the regional socio-political unrests, have thus weighing on Jordan’s
aggregate demand and economic growth. Although Jordan’s economy has achieved strong growth
in recent years after a number of key reforms were introduced by the government; yet, the
kingdom's economy still faces a major threat from soaring inflation; the kingdom's economic
growth is being offset by rising inflation which has hit all-time highs Group Research Dept. (2012).
However, This study advocated the results of some previous researches that showed a positive
effect of real interest rate on both national income and on (GDP) Bader and Malawi (2010).
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